A cluster Analysis for Binary Data Using Genetic Algorithms

  • Authors

    • Sabariah Saharan
    • Wong Yu Xian
    • Roberto Baragona
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.30.28174
  • Binary Data, Clustering, Genetic Algorithms.

  • Abstract

    This research was initially driven by the lack of clustering algorithms that focus on binary data. A promising technique to analyze this type of data, namely Genetic Clustering for Unknown K (GCUK) became the main subject in this research. GCUK was applied to cluster four binary data and there is a presence of an imbalanced data in one of the data sets. The results show that GCUK is an efficient and effective clustering algorithm compared to K-means. The other contribution is the capability of GCUK for clustering the unbalanced data. Standard clustering algorithms cannot simply be applied to this type of data sets as it can cause a misclassification results.

     

  • References

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  • How to Cite

    Saharan, S., Yu Xian, W., & Baragona, R. (2018). A cluster Analysis for Binary Data Using Genetic Algorithms. International Journal of Engineering & Technology, 7(4.30), 550-552. https://doi.org/10.14419/ijet.v7i4.30.28174

    Received date: 2019-03-03

    Accepted date: 2019-03-03

    Published date: 2018-11-30